davideroznowicz / twitter_popularity_prediction Goto Github PK

We developed a Random-Forest-based model to predict the popularity of a tweet about food.
We gathered our dataset through Twitter API: after querying our target users’ timelines and filtering out weakly-informative tweets, we ended up with about 15,000 of them, together with over 90 metadata-related variables, to which we added hundreds of text mining-derived features.
Since downloading and processing more than 1.6 GB of data had proven a computationally intensive task, an initial attempt in python was discarded and taken over by a much faster OpenMP version of a C implementation.

• If you want to see a nice report, presenting details about the implementation together with the final results, go to final report

• Instead, if you want to dig into the technical part and see the codes, go to the folder twitter